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from typing import Optional
from core.model_manager import ModelInstance
from core.rag.models.document import Document
class RerankRunner:
def __init__(self, rerank_model_instance: ModelInstance) -> None:
self.rerank_model_instance = rerank_model_instance
def run(self, query: str, documents: list[Document], score_threshold: Optional[float] = None,
top_n: Optional[int] = None, user: Optional[str] = None) -> list[Document]:
"""
Run rerank model
:param query: search query
:param documents: documents for reranking
:param score_threshold: score threshold
:param top_n: top n
:param user: unique user id if needed
:return:
"""
docs = []
doc_id = []
unique_documents = []
for document in documents:
if document.metadata['doc_id'] not in doc_id:
doc_id.append(document.metadata['doc_id'])
docs.append(document.page_content)
unique_documents.append(document)
documents = unique_documents
rerank_result = self.rerank_model_instance.invoke_rerank(
query=query,
docs=docs,
score_threshold=score_threshold,
top_n=top_n,
user=user
)
rerank_documents = []
for result in rerank_result.docs:
# format document
rerank_document = Document(
page_content=result.text,
metadata={
"doc_id": documents[result.index].metadata['doc_id'],
"doc_hash": documents[result.index].metadata['doc_hash'],
"document_id": documents[result.index].metadata['document_id'],
"dataset_id": documents[result.index].metadata['dataset_id'],
'score': result.score
}
)
rerank_documents.append(rerank_document)
return rerank_documents
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